1. Field of the Invention
This invention pertains generally to change detection in imagery, and more particularly to anomalous change detection in imagery.
2. Description of Related Art
With decreasing costs of acquiring overhead imagery, and an increasing variety of available image modalities (from video to hyperspectral), image analysts have the ability to see more of the world in more detail than ever before. For precisely the same reasons, image analysts also have more images than they can look at, let alone analyze, which makes the automated analysis of imagery an imperative.
While the automated understanding of imagery is an extremely challenging long-term goal, the best hope in the near term may be data triage —concede that every image cannot be fully analyzed, but at least identify those images that are most desperately in need of an analyst's attention. This is where change detection can help.
While single images are indeed difficult to analyze, pairs of images can actually be easier. With two images of the same scene, there is a lot of context built right into the data. As the problem goes from finding interesting things in images to finding interesting changes in image pairs, it becomes more tractable. On the other hand, even the limited aim of detecting changes in imagery is itself extremely challenging.
Change detection in imagery is of broad general interest, but it is especially useful in remote sensing. Using pictures taken from satellite or airborne platforms, accurate maps can be made of what is on the ground. These maps are valuable, but they are not static: new highways are built, new agricultural fields are planted, new housing is constructed, old warehouses are bulldozed, wetlands are encroached, forests are burned. And it is what has most recently changed that usually is most keenly of interest.
Change detection is important in other imagery too. Using pictures of the sky taken from ground-based telescopes, changes can indicate asteroids, flare stars, potentially even new astronomical phenomena. In practice, these changes usually indicate terrestrial phenomena and image artifacts that need to be filtered out.